ECE 4960 Fast Robots

Cornell, Fall 2020

Lecture slides

Lecture slides will be uploaded on this page. Recorded lectures are available via Canvas.

• Lecture 1 - Intro
• Lecture 2 - Transformation Matrices, In-class Assignment
• Lecture 3 - Sensors
• Lecture 4 - IMU
• Lecture 5 - PID intro
• Lecture 6 - PID continued and data types, you can find accumulated data from Lab 3 here.
• Lecture 7 - Noise and probability, Bayes theorem
• Lecture 8 - Bayes Filter I, In-class Assignment
• Lecture 9 - Bayes Filter II (In-class Assignment and Pre-lecture slides)
• Lecture 9a - Sensor Models
• Lecture 9b - Motion Models
• Lecture 10 - Navigation I, local navigation and map representations
• Lecture 11 - Navigation II, Graph construction, Potential functions, PRM, RRT, RRT interactive demo by Aaron Becker, UH
• Lecture 12 - Graph search
• Lecture 13 - Grid Localization, In-class Assignment
• Lecture 14 - Linear Systems
• Lecture 15 - Linearizing non-linear systems, controllability, Lab 9 Discussion
• Lecture 16 - Degrees of Controllability
• Lecture 17 - Inverted pendulum on a cart
• Lecture 18 - Lab discussion
• Lecture 19 - Guest lecture by Prof. Konidaris, Brown and Realtime Robotics
• Lecture 20 - Guest lecture by Prof. Ferrari, LISC, Cornell
• Lecture 21 - Guest lecture by Dr. Vasu Raman, Zipline robotics
• Lecture 22 - Recap